Skip to main content Accessibility help
×
Home

Predicting intramuscular fat, moisture and Warner-Bratzler shear force in pork muscle using near infrared reflectance spectroscopy

  • N. Barlocco (a1), A. Vadell (a1), F. Ballesteros (a2), G. Galietta (a2) and D. Cozzolino (a3)...

Abstract

Partial least-squares (PLS) models based on visible (Vis) and near infrared reflectance (NIR) spectroscopy data were explored to predict intramuscular fat (IMF), moisture and Warner Bratzler shear force (WBSF) in pork muscles (m. longissimus thoracis) using two sample presentations, namely intact and homogenized. Samples were scanned using a NIR monochromator instrument (NIRSystems 6500, 400 to 2500 nm). Due to the limited number of samples available, calibration models were developed and evaluated using full cross validation. The PLS calibration models developed using homogenized samples and raw spectra yielded a coefficient of determination in calibration (R2) and standard error of cross validation (SECV) for IMF (R2=0·87; SECV=1·8 g/kg), for moisture (R2=0·90; SECV=1·1 g/kg) and for WBSF (R2=0·38; SECV=9·0 N/cm). Intact muscle presentation gave poorer PLS calibration models for IMF and moisture (R2<0·70), however moderate good correlation was found for WBSF (R2=0·64; SECV=8·5 N/cm). Although few samples were used, the results showed the potential of Vis-NIR to predict moisture and IMF using homogenized pork muscles and WBSF in intact samples.

Copyright

Corresponding author

References

Hide All
Association of Official Analytical Chemists. 1990. Official methods of analysis of the Association of Official Analytical Chemists, 15th edition. Association of Official Analytical Chemists, Inc., Arlington, VA.
Ben-Gera, I. and Norris, K. H. 1968. Direct spectrophotometric determination of fat and moisture in meat products. Journal of Food Science 33: 6467.
Brøndum, J., Munck, L., Henckel, P., Karlsson, A., Tornberg, E. and Engelsen, S. B. 2000. Prediction of water holding capacity and composition of porcine meat by comparative spectroscopy. Meat Science 55: 177185.
Byrne, C. E., Downey, G., Troy, D. J. and Buckley, D. J. 1998. Non-destructive prediction of selected attributes of beef by near-infrared reflectance spectroscopy between 750 and 1098 nm. Meat Science 49: 399409.
Chrystall, B. B., Culioli, J., Demeyer, D., Honikel, K. O., Møller, O. J., Purslow, P., Schwagele, F., Shorthose, R. and Uytterhae-gen, J. 1994. Recommendation of reference methods for assessment of meat tenderness. Proceedings of 40th international congress of meat science and technology. P. SV06. The Hague, The Netherlands.
Clark, D. H. and Short, R. E. 1994. Comparison of AOAC and light spectroscopy analysis of uncooked ground beef. Journal of Animal Science 72: 925931.
Cozzolino, D., Brito, G. and San Julian, R. 2003. The use of near infrared reflectance spectroscopy to assess tenderness, colour and pH in longissimus muscle. Proceedings of the 48th international congress of meat science and technology, Rome, pp. 798799.
Cozzolino, D. and Murray, I. 2002. Effect of sample presentation and animal muscle species on the analysis of meat by near infrared reflectance spectroscopy. Journal of Near Infrared Spectroscopy 10: 3744.
Cozzolino, D., Murray, I., Scaife, J. R. and Paterson, R. 2000. Study of dissected lamb muscles by visible and near infrared reflectance spectroscopy for composition assessment. Animal Science 70: 417423.
Davis, C. E., Birth, G. S. and Townsend, W. E. 1978. Analysis of spectral reflectance for measuring pork quality. Journal of Animal Science 46: 634638.
Eggert, J. M., Depreux, F. F. S., Schinckel, A. P., Grant, A. L. and Gerrard, D. E. 2002. Myosin heavy chain isomorphs account for variation in pork quality. Meat Science 61: 117126.
Fernández, X., Monin, G., Talmant, A., Mourot, J. and Lebret, B. 1999. Influence of intramuscular fat content on the quality of pig meat. 1. Composition of the lipid fraction and sensory characteristics of m. longissimus lumborum. Meat Science 53: 5965.
Folch, J., Less, M. and Stanley, G. H. S. 1957. A simple method for the isolation and purification of total lipids in animal tissue. Journal of Biological Chemistry 226: 497501.
Geesink, G. H., Schreutelkamp, F. H., Frankhuizen, R., Vedder, H. W., Faber, N. M., Kranen, R. W. and Gerritzen, M. A. 2003. Prediction of pork quality attributes from near infrared reflectance spectra. Meat Science 65: 661668.
Hildrum, K. I., Isaksson, T., Naes, T., Nilsen, B. N., Rødbotten, M. and Lea, P. 1995. Near infrared reflectance spectroscopy in the prediction of sensory properties of beef. Journal of Near Infrared Spectroscopy 3: 8187.
Hildrum, K. I., Nilsen, B. N., Mielnik, M. and Naes, T. 1994. Prediction of sensory characteristics of beef by near infrared spectroscopy. Meat Science 38: 6780.
Honikel, K. O. 1998. Reference methods for the assessment of physical characteristic of meat. Meat Science 49: 447457.
Lanza, E. 1983. Determination of moisture, protein, fat and calories in raw pork, and beef by near infrared spectroscopy. Journal of Food Science 48: 471474.
Lawrie, R. A. 1985. Meat science, fourth edition. Pergamon Press, Oxford.
Leroy, B., Lambotte, S., Dotreppe, O., Lecocq, H., Istasse, L. and Clinquart, A. 2003. Prediction of technological and organoleptic properties of beef longissimus thoracis from near infrared reflectance and transmission spectra. Meat Science 66: 4554.
McCaig, T. N. 2002. Extending the use of visible/near infrared reflectance spectrophotometers to measure colour of food and agricultural products. Food Research International 35: 731736.
Martens, H. and Dardenne, P. 1998. Validation and verification of regression in small data sets. Chemometrics and Intelligent Laboratory Systems 44: 99106.
Martens, H. and Martens, M. 2000. Multivariate analysis of quality: an introduction. John Wiley and Sons, Chichester.
Martens, H. and Naes, T. 1996. Multivariate calibration. John Wiley and Sons Ltd, New York.
Mitsumoto, M., Maeda, S., Mitsuhashi, T. and Ozawa, S. 1991. Near infrared spectroscopy determination of physical and chemical characteristics in beef cuts. Journal of Food Science 56: 14931496.
Monin, G. 1998. Recent methods for predicting quality in whole meat Meat Science 49: S231S243
Mörlein, D., Rosner, F., Brand, S., Jenderka, K.-V. and Wicke, M. 2005. Non-destructive estimation of intramuscular fat content of the longissimus muscle of pork by means of spectral analysis of ultrasound echo signals. Meat Science 69: 187199.
Murray, I. 1986. The NIR spectra of homologous series of organic compounds. In NIR/NIT conference (ed. Hollo, J., Kaffka, K. J. and Gonczy, J. L.), pp. 1328. Akademiai Kiado, Budapest.
Naes, T., Isaksson, T., Fearn, T. and Davies, T. 2002. A user-friendly guide to multivariate calibration and classification. NIR Publications, Chichester, UK.
Oeckel, M. J., van, Warnants, N., Boucque Ch., V. 1999. Pork tenderness estimation by taste panel, Warner-Bratzler shear force and on-line methods. Meat Science 53: 259267.
Rødbotten, R., Nilsen, B. N. and Hildrum, K. I. 2000. Prediction of beef quality attributes from early post mortem near infrared reflectance spectra. Food Chemistry 69: 42436.
Park, B., Chen, Y. R., Hruschka, W. R., Shackelford, S. D. and Koohmaraie, M. 1998. Near infrared reflectance analysis for predicting beef longissimus tenderness. Journal of Animal Science 76: 21152120.
Strayer, L. 1995. Biochemistry, fourth edition. W.H. Freeman and Co., New York.
Swatland, H. J. 1995. On line evaluation of meat. Technomic Publishing Co., Lancaster, USA.
Swatland, H. J. 1986a. Post-mortem spectrophotometry of color intensity of pork and beef using quartz optical fibres. Meat Science 17: 97106.
Swatland, H. J. 1986b. Color measurements on pork and veal carcasses by fiber optic spectrophotometry. Canadian Institute of Food Science and Technology 19: 170173.
The Unscrambler. 1996. User's guide, version 6.0. CAMO AS, Trondheim, Norway.
Vedder, H. W., Merks, J. W. M., Klein, W. J. H., de Reimert, H. G. M., Frankhuizen, R., Broek, W. H. A. M., van den Lambooij, E. E. 2005. Perspective of NIRS measurement early post-mortem for prediction of pork quality. Meat Science 69: 417423.
Venel, C., Mullen, A. M., Downey, G. and Troy, D. 2001. Prediction of tenderness and other quality attributes of beef by near infrared reflectance spectroscopy between 750 and 1100 nm: further studies. Journal of Near Infrared Spectroscopy 9: 185198.
Williams, P. C. 2001. Implementation of near infrared technology. In New infrared technology in the agricultural and food industries (ed. Williams, P. C. and Norris, K. H.), pp. 145171. American Association of Cereal Chemists, St Paul, MN.

Keywords

Related content

Powered by UNSILO

Predicting intramuscular fat, moisture and Warner-Bratzler shear force in pork muscle using near infrared reflectance spectroscopy

  • N. Barlocco (a1), A. Vadell (a1), F. Ballesteros (a2), G. Galietta (a2) and D. Cozzolino (a3)...

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed.